Eric D. Manley

All-Optical Network Coding

We investigate the application of network coding to all-optical networks from both the algorithmic and infrastructural perspectives. We study the effectiveness of using network coding for optical-layer dedicated protection of multicast traffic that provides robustness against link failures in the network. We present a heuristic for solving this problem and compare it with both inefficient optimal methods and non-network-coding approaches. Our experiments show that our heuristic provides near-optimal performance while significantly outperforming existing approaches for dedicated multicast protection. We also propose architectures for specialized all-optical circuits capable of performing the processing required for network coding and show how these devices can be effectively deployed in an all-optical multicast network.

Localization and Tracking in Sensor Systems

In this paper, we survey the current state-of-art of localization and tracking. Our emphasis is on algorithms and systems used in sensor networks. We categorize localization and tracking systems into a hierarchical taxonomy based on characteristics of the objects being tracked, the application environments, and the sensor network technologies. Ideas leading to new directions for future research are briefly discussed

Minimizing network cost in all-optical networks

The problem of minimizing the total network cost of an optical network topology by efficient selection of switching sites, size of optical switches, and optical links is investigated in this paper. The problem investigated is NP—hard. Therefore, we develop an efficient heuristic to approximate the solution in polynomial time. A mixed integer quadratic programming (MIQP) formulation of the problem is also presented to find the optimal network cost and compute the efficiency of the heuristic. The total network cost calculated by the heuristic in the experiments is within 19% of its optimal value. Moreover, the total network cost in half of the test problems is within 6% of its optimal value. The heuristic solves the problem with 20 node topologies in less than a second. However, the commercial optimization software can not solve any problem with more than 10 nodes even in two weeks.

Design of an all-optical WDM lightpath concentrator

A concentrator is a switch in which the number of input fibers is strictly greater than the number of output fibers. Thus, a concentrator drops some input signals and switches each of the remaining signals to output fibers on possibly different wavelengths. If the switching is done in the electronic domain, it is called an electronic concentrator or simply a concentrator. If the switching is performed in all-optical domain, then it is called an all-optical lightpath concentrator or simply lightpath concentrator. With the advancement of wavelength division multiplexing (WDM) technology, there has been an exponential growth in the size of interconnects, their complexity, the number of necessary optical-electrical-optical (O/E/O) converters, and their cost. There is a large mismatch between the capacity and speed of optical transmission compared with electronic transmission which results in a bottleneck of the electronic switches and concentrators in WDM networks. This mismatch motivates design of all-optical switches and lightpath concentrators which can keep data in the optical domain, eliminating the need for costly and inefficient O/E/O conversions. There are several practical deployments of optical networks where it is necessary to switch signals from N fibers to M fibers, where N > M [1]. For example, the function of a hub in metro networks is to collect N lightpaths from several regional hubs and transfer them to M lightpaths in the backbone network. Thus, a hub is a lightpath concentrator [1]. Lightpath concentrators have also been used in the design of all-optical switch architectures [2], [3], [4]. With the advancement of WDM technologies, there has been a need for cost effective WDM interconnects. WDM crossconnects typically have separate stages for space and wavelength switching. These designs are expensive, and the switching costs increase significantly with the increase in the number of lightpaths carried by the fiber. A new paradigm for WDM interconnect design is evolving in which space and wavelength switching is performed simultaneously and seamlessly [2], [3]. This design for WDM crossconnects eliminates the need for separate wavelength conversion stages. In this paper, we present a design of an all-optical lightpath concentrator based on wavelength exchanging optical crossbars (WOC) and WDM Crossbar Switches [2], [3]. The design of an all-optical lightpath concentrator presented in this paper makes use of WOC properties and can similarly achieve a balance between wavelength switching and conversion costs and does not require a separate wavelength conversion stage.

LIPS: Learning Based Indoor Positioning System using mobile phone-based sensors

In this paper we investigate the problem of localizing a mobile device based on readings from its sensors utilizing machine learning methodologies. We consider a real-world environment, collect a dense set of 3110 datapoints, and examine the performance of a substantial number of machine learning algorithms. We found algorithms that have a mean error as accurate as 0.76 meters, outperforming other indoor localization systems. We also propose a hybrid instance-based approach that results in a speed increase by a factor of ten with no loss of accuracy in a live deployment over standard instance-based methods. Further, we determine how less dense datasets affect accuracy, important for use in real-world environments. Finally, we demonstrate that these approaches are appropriate for real-world deployment by evaluating their performance in an online, in-motion experiment. The Learning Based Indoor Positioning System (LIPS) Android application source has been made available on the web.In this paper we investigate the problem of localizing a mobile device based on readings from its embedded sensors utilizing machine learning methodologies. We consider a realworld environment, collect a large dataset of 3110 datapoints, and examine the performance of a substantial number of machine learning algorithms in localizing a mobile device. We have found algorithms that give a mean error as accurate as 0.76 meters, outperforming other indoor localization systems reported in the literature. We also propose a hybrid instance-based approach that results in a speed increase by a factor of ten with no loss of accuracy in a live deployment over standard instance-based methods, allowing for fast and accurate localization. Further, we determine how smaller datasets collected with less density affect accuracy of localization, important for use in real-world environments. Finally, we demonstrate that these approaches are appropriate for real-world deployment by evaluating their performance in an online, in-motion experiment.

Low complexity all-optical network coder architecture

Network coding, a networking paradigm in which different pieces of data are coded together at various points along a transmission, has been proposed for providing a number of benefits to networks including increased throughput, robustness, and security. For optical networks, the potential for using network coding to provide survivability is especially noteworthy as it may be possible to allow for the ultra-fast recovery time of dedicated protection schemes with the bandwidth efficiency of shared protection schemes. However, the need to perform computations at intermediate nodes along the optical route leads to the undesirable necessity of either electronically buffering and processing the data at intermediate nodes or outfitting the network with complex photonic circuits capable of performing the computations entirely within the optical domain. In this paper, we take the latter approach but attempt to mitigate the impact of the device complexity by proposing a low-complexity, all-optical network coder architecture. Our design provides easily scalable, powerful digital network coding capabilities at the optical layer, and we show that existing network coding algorithms can be adjusted to accommodate it.

Selection Of Switching Sites In All-Optical Network Topology Design

In this paper, we consider the problem of topology design for both unprotected and one-link protected all-optical networks. We investigate the problem of selecting switching sites to minimize total cost of the network. The cost of an optical network is expressed as a sum of three main factors: the site cost, the link cost, and the switch cost. For unprotected networks with linear cost model, we present a mixed integer linear programming (MILP) formulation of the problem. We also present an efficient heuristic to approximate the solution. The experimental results show good performance of the linear cost model heuristic. In 16% of the experiments with 10 nodes network topologies, the linear cost model heuristic had no error. Moreover, for 54% and 86% of the experiments with 10 nodes network topologies, the linear cost model heuristic’s solution is within 2% and 5% of its optimal value respectively. Finally, we extend our approach to one-link protected networks, and present an efficient survivable heuristic, and representative experimental results.